Matematicheskaya Biologiya i Bioinformatika
RUS  ENG    JOURNALS   PEOPLE   ORGANISATIONS   CONFERENCES   SEMINARS   VIDEO LIBRARY   PACKAGE AMSBIB  
General information
Latest issue
Archive
Impact factor

Search papers
Search references

RSS
Latest issue
Current issues
Archive issues
What is RSS



Mat. Biolog. Bioinform.:
Year:
Volume:
Issue:
Page:
Find






Personal entry:
Login:
Password:
Save password
Enter
Forgotten password?
Register


Matematicheskaya Biologiya i Bioinformatika, 2023, Volume 18, Issue 1, Pages 15–32
DOI: https://doi.org/10.17537/2023.18.15
(Mi mbb506)
 

This article is cited in 1 scientific paper (total in 1 paper)

Bioinformatics

Application of virtual screening and molecular modeling technologies to identify potential SARS-CoV-2 main protease inhibitors

A. M. Andrianova, K. V. Fursb, A. V. Goncharb, L. H. Aslanyanc, A. V. Tuzikovb

a Institute of Bioorganic Chemistry, National Academy of Sciences of Belarus, Minsk, Republic of Belarus
b United Institute of Informatics Problems, National Academy of Sciences of Belarus, Minsk, Republic of Belarus
c Institute for Informatics and Automation Problems of National Academy of Sciences of Republic of Armenia, Yerevan, Armenia
Full-text PDF (838 kB) Citations (1)
References:
Abstract: A virtual screening of the molecular library of biologically active compounds was carried out to identify potential inhibitors of SARS-CoV-2 main protease (Mpro) which plays an important role in the process of virus replication. Using molecular docking and molecular dynamics, the binding energy of these compounds to the catalytic site of the enzyme was assessed, resulting in six molecules that exhibited high chemical affinity for SARS-CoV-2 Mpro. This is evidenced by the low values of the binding free energy of the ligand/Mpro complexes comparable with those predicted for the potent non-covalent SARSCoV-2 Mpro inhibitor using the identical computational protocol. Based on the data obtained, it was concluded that the identified compounds have a good therapeutic potential for inhibiting the catalytic activity of the enzyme and form promising basic structures for the development of new effective drugs against COVID-19.
Key words: SARS-CoV-2, main protease, virtual screening, molecular docking, molecular dynamics, antiviral drugs.
Funding agency Grant number
Belarusian Republican Foundation for Fundamental Research Ф21АРМГ-001
Alliance of International Science Organizations (Peking, China) ANSO-CR-PP-2021-04
Received 27.01.2023, 12.02.2023, Published 22.02.2023
Document Type: Article
Language: Russian
Citation: A. M. Andrianov, K. V. Furs, A. V. Gonchar, L. H. Aslanyan, A. V. Tuzikov, “Application of virtual screening and molecular modeling technologies to identify potential SARS-CoV-2 main protease inhibitors”, Mat. Biolog. Bioinform., 18:1 (2023), 15–32
Citation in format AMSBIB
\Bibitem{AndFurGon23}
\by A.~M.~Andrianov, K.~V.~Furs, A.~V.~Gonchar, L.~H.~Aslanyan, A.~V.~Tuzikov
\paper Application of virtual screening and molecular modeling technologies to identify potential SARS-CoV-2 main protease inhibitors
\jour Mat. Biolog. Bioinform.
\yr 2023
\vol 18
\issue 1
\pages 15--32
\mathnet{http://mi.mathnet.ru/mbb506}
\crossref{https://doi.org/10.17537/2023.18.15}
Linking options:
  • https://www.mathnet.ru/eng/mbb506
  • https://www.mathnet.ru/eng/mbb/v18/i1/p15
  • This publication is cited in the following 1 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
     
      Contact us:
     Terms of Use  Registration to the website  Logotypes © Steklov Mathematical Institute RAS, 2024